Here we import our data and make some summary plots.
EEG Data
Importing the primary EEG data set. This is odd-harmonic filtered data from region-of-interest consisting of six electrodes over occipital cortex.
## Observations: 400
## Variables: 3
## $ wg <chr> "P2", "PM", "PG", "CM", "PMM", "PMG", "PGG", "CMM", "P4"…
## $ subject <chr> "s01", "s01", "s01", "s01", "s01", "s01", "s01", "s01", …
## $ rms <dbl> 0.4013, 0.6555, 0.5547, 0.7635, 0.9185, 0.7285, 0.4320, …
It’s clearly skewed, and negative display duration are impossible, so will fit a glm with family = 'lognormal.
Threshold Data
Here we import that data and select the columns that we’re interested in. Threshold gives the required display duration (in seconds) for the two stimuli to allow for accurate discrimination.
## Observations: 186
## Variables: 3
## $ subject <chr> "person10", "person10", "person10", "person10", "perso…
## $ wg <chr> "CM", "CMM", "P2", "P3", "P31M", "P3M1", "P4", "P4G", …
## $ threshold <dbl> 0.74125, 0.20216, 0.47697, 0.35012, 0.24529, 0.19022, …
As above, a summary of the data.
Again, we have a skewed distribution, so will fit with family = 'lognormal'.
Control Data
In addition to the primary EEG data set, we are also importing two control data sets which are (a) even harmonic data from the same occipital electrodes, and (b) odd harmonic data
from six parietal electrodes (see Figure 1.1 and the main paper).